Predictive modeling and evolution analysis of residual stress profiles in TC17 titanium alloy under cutting and pre-mixed abrasive waterjet peening

In the manufacturing of aerospace components, cutting and strengthening processes are essential steps. A well-distributed surface residual stress field can effectively suppress the initiation and propagation of fatigue cracks, significantly improving the fatigue life of components. This paper proposes two predictive models to assess the residual stress distribution in TC17 alloy after cutting and strengthening treatments. Initially, stress characteristic parameters were identified, and a predictive model based on these parameters was developed. Systematic experiments were conducted to analyze the effects of cutting and pre-mixed abrasive waterjet peening (PAWJP) process parameters on the characteristic parameters, and the sensitivity of each characteristic parameter to the process parameters was further evaluated. Additionally, the residual stress distribution curve was decomposed into a cosine function and an exponential function, leading to the development of a cosine decay function model. This model, which is simple yet effective, can predict the entire residual stress field. Using the two models, residual stress fields resulting from cutting and PAWJP treatments were predicted by the proposed models, showing strong agreement with measurements. Finally, two independent cutting and PAWJP validation experiments were conducted. The maximum relative error among the extracted characteristic descriptors was below 19%; in absolute terms, the deviations were within 30 MPa for stress-magnitude descriptors and within 22.72 μm for depth-related descriptors. Overall, the proposed models were validated and can support efficient prediction and optimization of depth resolved residual stress distributions within the calibrated process window.